The inability to understand the importance of data is common to all the naysayers who refuse to accept that autonomous vehicles will be a reality far sooner than the current time frames suggest: they still believe machines are immutable objects. Nothing could be further from the truth: machines are now capable of automatically incorporating learning, of acquiring new data, processing it and acting accordingly based on rules derived from the analysis of that data. They can also operate on the basis of data generated by other machines and from any strategies we choose to add to the mix. In the case of companies such as Tesla or Waymo, these strategies not only use the data that their vehicle fleets generate - owned and managed in the case of Waymo, or in the hands of its customers, in the case Tesla - but also include data obtained from a range of tests and the use of virtual environments to explore every possibility their vehicles may encounter.

Even before it leaves the factory, an autonomous vehicle has dealt with more road situations and problems than the best human drivers will have and will be able to solve them expertly and efficiently.

Data analysis will impact on just about every sector you can think of, providing the company that adopt it with the key competitive advantage. We are fast reaching a point where business is not about lending more money, selling more insurance policies or providing more courses than anyone else: it’s about how much information businesses are able to extract from their activities and how they can process it to improve their efficiency.

The issue here is not whether Tesla or Waymo’s data strategy is better, more efficient or faster: the important thing is that these companies owe their success to having a proper data strategy. Has your company turned data, its generation and its analysis, into its competitive weapon yet? Probably not: the vast majority of managers have not yet grasped the need for a data strategy: and not just any data strategy, but a better one than your competitors’. In short, we now compete by generating data, in finding ways to obtain more data, and through developing techniques that allow us to analyze it so we can extract better learning performance. Welcome to the new competitive variable: get on the program or get used to a slow but inexorable loss of competitiveness.